Distribution of tourists within urban heritage destinations: a hot spot/cold spot analysis of TripAdvisor data as support for destination management (original) (raw)
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The aim of this article is to answer the question of whether social networking sites can be an effective source of data, useful in the context of local tourism planning. The first part of the article contains a presentation of the role of social media in the tourism industry, a synthetic discussion of the most common topics of research related to the use of social media in tourism, and also characteristic of the TripAdvisor social network, which is the subject of the study. The second part presents the results of a study conducted using the website, covering the 30 most popular hotels, restaurants and tourist attractions in Poznan. The results contain a comment about the risks associated with the analysis of this type of data, as well as possible future directions of research.
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Big Data and Innovation in Tourism, Travel, and Hospitality, 2019
Social media networks are a resource for valuable knowledge about tourist destinations through the collection of data by Location-Based Social Networks (LBSN). A major problem is the lack of knowledge in respect to the visitors’ views about a destination, as well as the fact that the visitors’ behavior needs and preferences are not visible. Many enterprises and local authorities are still using traditional methods for acquiring knowledge to make strategic decisions, by collecting data from questionnaires. Nonetheless, this process, despite its benefits, is short-lived and the number of the participants is small compared to the number of visitors. This chapter discusses a methodology for the extraction, association, analysis, and visualization of data derived from LBSNs. This provides knowledge of visitor behaviors, impressions and preferences for tourist destinations. A case study of Crete in Greece is included, based upon visitors’ posts and reviews, nationality, photos, place rankings, and engagement.
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Big data analysis, especially of user generated data, is an innovative data collection method in tourism research. This paper attempts to explain how analysis of user generated content helps to map and understand cultural landscapes in a destination. Using data obtained from TripAdvisor a two-step analysis is conducted in order to map spatial behavior of reviewers at the destination and to use review behavior patterns to understand the shaping of the cultural landscape. Three case studies in which the urban cultural landscape is both a primary tourist attraction as well as an important part of local identity are compared, namely Antwerp (Belgium), Bolzano (Italy) and Kraków (Poland) and each of these destinations can be positioned at a different maturity level when applying the tourist area life cycle model by Butler. The results of the hot spot analysis show that there exists a correlation between the maturity of the destination and the review behavior, both in intensity as in perception of quality of services. An intensive use of a relatively small part of the historic center of a heritage destination and in this zone the presence of a cluster of facilities offering low service quality was found to indicate a mature destination and can be distinguished by applying geographical Big Data analysis on review behavior. Finally, this paper explains how user generated content can be used in mapping spatial behavior of tourists in urban cultural landscapes and what the limitations to such studies are.